Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to build an AI‑enhanced quality‑assurance (QA) platform that blends Side’s deep industry experience with Modl.ai’s cutting‑edge machine‑learning capabilities. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later. Its founder, Christoffer Holmgard, explains that earlier attempts at AI‑driven QA required developers to hand over entire game builds or even source code to a testing service.
Those “integration‑based” approaches relied on plugins and SDKs that created significant friction, making the process cumbersome and, over time, impractical. The new solution eliminates the need for any internal access to the game’s code.
Instead, developers supply the product exactly as they would hand it to a human tester—or ultimately to the consumer. The game runs on a device that mirrors the target platform, while the AI watches the screen, simulates key actions, records every visual and input event, and then passes the resulting data set to a second AI layer that flags potential bugs.
That layer escalates each issue to a human reviewer, asking whether the finding warrants further action. The first phase of the workflow is what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant materials, then converse with the AI in natural language.
This dialogue helps the system form a contextual understanding of the game’s mechanics, narrative, and visual style. Holmgard emphasizes that the interaction is entirely conversational—text, images, and documents are all ingested without the need for technical integration. Once the AI has a solid grasp of the game, developers specify the testing objectives.
These can range from classic test cases—such as verifying level loading or UI responsiveness—to novel scenarios that are specifically crafted to leverage the AI’s strengths. Holmgard notes that human expertise remains essential at this stage; testers must shape prompts and guide the AI’s language so that it performs the desired actions correctly.
During a testing session, which Modl.ai refers to as a “run,” the system automatically generates bug reports. Each report includes textual descriptions, short video snippets that serve as visual evidence, and comprehensive log data.
These artifacts are then handed to a qualified QA specialist, who reviews the findings and decides how to incorporate them into the development pipeline. One of the enduring challenges in automated testing is distinguishing a genuine defect from an intentional feature. Holmgard explains that continuous feedback from human QA professionals helps the AI refine its judgment.
When testers label a finding as a bug, not a bug, or a design choice, the system learns from those annotations, gradually improving its ability to make nuanced decisions. Side sees this partnership as a pathway to elevate its workforce. Rather than remaining confined to repetitive testing tasks, QA staff can evolve into AI engineers who design prompts, interpret AI outputs, and fine‑tune models. Martin McBride, Side’s chief commercial officer, says this shift “moves our people up the value chain,” offering higher salaries, new career trajectories, and the possibility of bringing jobs back to regions where low‑cost testing has previously migrated.
McBride also stresses that AI is not intended to replace human testers but to augment them. By automating mundane, repetitive checks—such as smoke tests for each new build—testers can focus on strategic analysis, creative exploration, and higher‑level problem solving.
Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment, noting that many current tests are tedious and could be handled more efficiently by machines, freeing humans to assess gameplay quality and conduct inventive testing approaches. The collaboration acknowledges the current limits of the technology.
Oliver Deslandes, Side’s chief operating officer, points out that the AI solution works best with simpler titles—puzzle games, card games, or other experiences with repeatable mechanics—rather than fast‑paced, 3D open‑world or fighting games. The team is targeting developers who are willing to experiment with pilots, understand the iterative nature of the project, and accept that results may evolve over time.
Overall, Side and Modl.ai envision a future where AI serves as a “sliding scale” tool: the more sophisticated the AI component, the less manual effort required, yet a human will always remain in the loop to verify, interpret, and make final decisions. This philosophy underpins their joint effort, aiming to reduce errors, speed up testing cycles, and ultimately deliver higher‑quality games while preserving the essential role of skilled QA professionals. In summary, the six‑month MOU binds Side and Modl.ai to co‑develop an AI‑driven QA platform that respects the nuances of game design, minimizes friction for developers, and creates new, higher‑value roles for QA talent.
The partnership reflects a broader industry trend toward intelligent automation that complements, rather than supplants, human expertise, promising a more efficient and rewarding testing ecosystem for the gaming world.